Corpus-Based Teaching of German Compound Nouns and Lexical Bundles for Improving Academic Writing Skills
Datos Bibliográficos
| ID | 6159243 |
|---|---|
| Autores | Marina Kogan (0000-0002-7519-2161, Peter the Great St. Petersburg Polytechnic University), Anna Yaroshevich (Peter the Great St. Petersburg Polytechnic University), Olga Ni (Peter the Great St. Petersburg Polytechnic University) |
| Año | 2018 |
| Volumen | 58 |
| Número | 58 |
| Fecha de publicación | 2018-11-02 |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Lidil (JOURNAL) |
| Identificadores de la revista | ISSN: 1146-6480 • E-ISSN: 1960-6052 |
| Editorial | OpenEdition (PUBLISHER) |
| DOI | 10.4000/lidil.5438 |
| OpenAlex | W2914019016 |
| Idioma | EN |
| Citas recibidas | 1 |
| Referencias citadas | 30 |
This study highlights the problem of the lack of German specialized corpora for German for specific purposes (GSP) courses for engineering students and describes a project aiming at the development of such a corpus, the Kod.ING corpus. The authors show the relevance of the Kod.ING corpus in meeting the needs of Master's degree engineering students at St Petersburg Polytechnic University who are studying lower-level German. At the preliminary stage of the pedagogical experiment, nine compound nouns and eight lexical bundles were selected from the Kod.ING corpus. These were taught to students through hands-on and hands-off data-driven learning (DDL) activities. The immediate and delayed post-tests proved the effectiveness of short DDL interventions in terms of acquisition of target vocabulary. The follow-up survey revealed students' particular interest in hands-on activities with the Russian National Corpus (RNC). In conclusion, further research and pedagogical applications are suggested
Compound · German · Linguistics · Natural language processing · Noun · Computer Science · Discourse Analysis in Language Studies · Philosophy · Psychology · Second Language Acquisition and Learning · Text Readability and Simplification · Artificial Intelligence
| Citas por año | 0,2 |
|---|---|
| Intervalo de citas | 2021 - 2021 (1) |
| Altamente citado | No |